Knowledge Graph Agentic AI Architect - Cambridge, MA (Hybrid)

Job Title : Knowledge Graph Agentic AI Architect
Location : Cambridge, MA (Hybrid)
 

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, AI, or a related field.
• 12+ years of experience in Data Architecture, AI/ML, Enterprise Data Platforms, or Data Engineering.
• Strong expertise in SQL database architecture, data modeling, query optimization, indexing, ETL/ELT design, and data warehousing.
• Hands-on experience with Knowledge Graphs, graph databases, ontology design, and semantic technologies.
• Experience with LLMs, vector databases, RAG architectures, and Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel.
• Proficiency in Python, SQL, APIs, cloud services (AWS, Azure, or Google Cloud Platform), and modern data engineering tools.
• Strong understanding of enterprise architecture, data governance, and AI solution design.

Preferred Skills

• Experience with Life Sciences, Healthcare, or other regulated industries.
• Familiarity with MLOps, LLMOps, and AI monitoring frameworks.
• Strong stakeholder management and technical leadership skills.

Key Responsibilities

• Design and implement enterprise Knowledge Graph solutions using Neo4j, Amazon Neptune, or similar graph technologies.
• Architect scalable relational and analytical data platforms using SQL Server, PostgreSQL, MySQL, Snowflake, or cloud-native databases.
• Develop ontologies, semantic models, taxonomies, and entity relationship frameworks.
• Design Agentic AI solutions leveraging LLMs, multi-agent frameworks, RAG, Graph RAG, and autonomous workflows.
• Define enterprise data architecture, including data lakes, warehouses, vector databases, and metadata management.
• Build scalable data ingestion, transformation, enrichment, and knowledge extraction pipelines.
• Establish standards for data governance, security, performance optimization, observability, and AI reliability.
• Drive innovation through adoption of emerging AI, graph, and data technologies.